Development of a deep learning model for automated detection of calcium pyrophosphate deposition in hand radiographs
A combined deep-learning model detecting CPPD at the TFCC and MCP-2/3 joints in hand radiographs provides the highest diagnostic performance. The algorithm could be used to screen larger OA or RA databases or electronic medical records for CPPD cases. Future work includes dataset expansion and validation with external datasets.
Authors
- Guillaume Fahrni (ORCID: https://orcid.org/0000-0003-1583-9602)
- Thomas Hügle (ORCID: https://orcid.org/0000-0002-3276-9581)
- Fabio Becce (ORCID: https://orcid.org/0000-0001-8444-8504)
- Tobias Manigold (ORCID: https://orcid.org/0009-0006-6369-1963)
- E. Rosoux
- Deborah Markham
Institutions
- University of Bern (CH)
- University Hospital of Bern (CH)
- University of Lausanne (CH)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2024-10-23
- DOI
- https://doi.org/10.3389/fmed.2024.1431333
- Citations
- 3
- Primary Topic
- Rheumatoid Arthritis Research and Therapies
- Type
- article
- Field-Weighted Citation Impact
- 1.41
Funders
- Université de Lausanne